High freezing sensitivity of legumes relative to other herbaceous species in northern temperate plant communities
Bibliographic record
Abstract
BACKGROUND AND AIMS: Reduced snow cover and increased air temperature variability are predicted to expose overwintering herbaceous plants to more severe freezing in some northern temperate regions. Legumes are a key functional group that may exhibit lower freezing tolerance than other species in these regions, but this trend has been observed only for non-native legumes. Our aim was to confirm if this trend is restricted to non-native legumes or whether native legumes in these regions also exhibit low freezing tolerance. METHODS: First, we transplanted legumes (five non-native species and four native species) into either an old field (non-native) or a prairie (native) and used snow removal to expose the plots to increased soil freezing. Second, we grew plants in mesocosms (old field) and pots (prairie species) and exposed them in controlled environment chambers to a range of freezing treatments (control, 0, -5 or -10 °C) in winter or spring. We assessed freezing responses by comparing differences in biomass, cover and nodulation between freezing (or snow removal) treatments and controls. KEY RESULTS: Among legume species, lower freezing tolerance was positively correlated with a lower proportion of nodulated plants and active nodules, and under controlled conditions, freezing-induced reductions in above-ground biomass were lower on average in native legumes than in non-native legumes. Nevertheless, both non-native and native legumes (except Desmodium canadense) exhibited greater reductions in biomass in response to increased freezing than their non-leguminous neighbours, both in controlled environments and in the field. CONCLUSIONS: These results demonstrate that both native and non-native legumes exhibit low freezing tolerance relative to other herbaceous species in northern temperate plant communities. By reducing legume biomass and nodulation, increased soil freezing could reduce nitrogen inputs into these systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".